4 ms·

All we need is something like Qwen3-coder-next but at Kimi K2.6 ability so it runs on laptop workstation hardware and we are set...soon?

wolttam 5mo ago
In 2023 GPT-4 was allegedly 1.8T parameters. In 2026 we have ~100x smaller models (10-20B) that handily outperform it, and can indeed run on a laptop.
- rectang 5mo ago
  How does "outperform" translate to the propensity of an LLM to hallucinate?
  - operatingthetan 5mo ago
    There seems to be a mass delusion about how capable SOTA models actually are. That's my only explanation for how poorly I find them performing in basic knowledge tasks compared to how others describe their prowess.
    - rectang 5mo ago
      I understand you to be implying that I shouldn't trust my perception that there's a meaningful difference in how much different models hallucinate. I will take that under advisement, but I am still interested in the answer to my original question.
      - operatingthetan 5mo ago
        >I understand you to be implying that I shouldn't trust my perception that there's a meaningful difference in how much different models hallucinate. Nope. Also I'm not GP.
- WanderPanda 5mo ago
  It highly depends on the task. For math and coding, sure. But for knowledge tasks GPT-4 is wayy better than even SOTA ~100B models. For my knowledge test cases the lines get blurry at >400B
unshavedyak 5mo ago
I am eagerly awaiting being able to run a strong local model. I'd hand Apple $5k right now for a Claude in a box. I know the cost might not be there now, just saying that is around my ideal price point. $10k might even be worth it - but i'm assuming that the more expensive it is the beefier it is too, which also means more electricity.. and i already run ~6 computers/servers in my house. If a power surge happens i'm going to go live in the woods lol.
- DANmode 5mo ago
  You can run 6-12 month old state of the art models for that type of money, like, yesterday.
  - unshavedyak 5mo ago
    Yea, but i don't consider them good enough. I barely consider SOTA good enough. I'm hoping that by the time the rugpull happens with SOTA (claude/etc) that at-home will be in the 4.7-5.5 range? We'll see.
    - DANmode 5mo ago
      They were good enough 6-12 months ago. Maybe your tooling is what’s keeping you from your dream.
- atonse 5mo ago
  I would do the same but my issue is that the models are changing so fast, so I don't want to be left out of the next model cuz it only runs on an even newer GPU or something like that. But maybe my limited understanding is thinking of this wrong.
  - JamesLeonis 5mo ago
    I wouldn't worry about hardware. I've run the latest local models over the last year, including the recent Qwen 3.6 30B A3B, on a 9yo GTX 1080 and 32G RAM I have lying around[0]. If I can do that I don't think hardware will be a problem for you in the near term. The only updates I've needed were to Llama.cpp when a new class of model was released. [0]: In my case, I want to see how local models perform on limited hardware, sacrificing context size and intelligence compared to SOTA models, so I have to really limit my expectations.

wolttam 5mo ago

In 2023 GPT-4 was allegedly 1.8T parameters. In 2026 we have ~100x smaller models (10-20B) that handily outperform it, and can indeed run on a laptop.

rectang 5mo ago
How does "outperform" translate to the propensity of an LLM to hallucinate?
- operatingthetan 5mo ago
  There seems to be a mass delusion about how capable SOTA models actually are. That's my only explanation for how poorly I find them performing in basic knowledge tasks compared to how others describe their prowess.
  - rectang 5mo ago
    I understand you to be implying that I shouldn't trust my perception that there's a meaningful difference in how much different models hallucinate. I will take that under advisement, but I am still interested in the answer to my original question.
    - operatingthetan 5mo ago
      >I understand you to be implying that I shouldn't trust my perception that there's a meaningful difference in how much different models hallucinate. Nope. Also I'm not GP.
WanderPanda 5mo ago
It highly depends on the task. For math and coding, sure. But for knowledge tasks GPT-4 is wayy better than even SOTA ~100B models. For my knowledge test cases the lines get blurry at >400B

unshavedyak 5mo ago

I am eagerly awaiting being able to run a strong local model. I'd hand Apple $5k right now for a Claude in a box. I know the cost might not be there now, just saying that is around my ideal price point. $10k might even be worth it - but i'm assuming that the more expensive it is the beefier it is too, which also means more electricity.. and i already run ~6 computers/servers in my house. If a power surge happens i'm going to go live in the woods lol.

DANmode 5mo ago
You can run 6-12 month old state of the art models for that type of money, like, yesterday.
- unshavedyak 5mo ago
  Yea, but i don't consider them good enough. I barely consider SOTA good enough. I'm hoping that by the time the rugpull happens with SOTA (claude/etc) that at-home will be in the 4.7-5.5 range? We'll see.
  - DANmode 5mo ago
    They were good enough 6-12 months ago. Maybe your tooling is what’s keeping you from your dream.
atonse 5mo ago
I would do the same but my issue is that the models are changing so fast, so I don't want to be left out of the next model cuz it only runs on an even newer GPU or something like that. But maybe my limited understanding is thinking of this wrong.
- JamesLeonis 5mo ago
  I wouldn't worry about hardware. I've run the latest local models over the last year, including the recent Qwen 3.6 30B A3B, on a 9yo GTX 1080 and 32G RAM I have lying around[0]. If I can do that I don't think hardware will be a problem for you in the near term. The only updates I've needed were to Llama.cpp when a new class of model was released. [0]: In my case, I want to see how local models perform on limited hardware, sacrificing context size and intelligence compared to SOTA models, so I have to really limit my expectations.